Conventional speech coding methods are generally based on single-channel speech signals. An example is the speech coding used in a connection between a regular telephone and a cellular telephone. Speech coding is used on the radio link to reduce bandwidth usage on the frequency limited air-interface. Well known examples of speech coding are PCM (Pulse Code Modulation), ADPCM (Adaptive Differential Pulse Code Modulation), sub-band coding, transform coding, LPC (Linear Predictive Coding) vocoding, and hybrid coding, such as CELP (Code-Excited Linear Predictive) coding [1-2].
In an environment where the audio/voice communication uses more than one input signal, for example a computer workstation with stereo loudspeakers and two microphones (stereo microphones), two audio/voice channels are required to transmit the stereo signals. Another example of a multi-channel environment would be a conference room with two, three or four channel input/output. This type of applications is expected to be used on the Internet and in third generation cellular systems.
General principles for multi-channel linear predictive analysis-by-synthesis (LPAS) signal encoding/decoding are described in [3]. However, the described principles are not always optimal in situations where there is a strong variation in the correlation between different channels. For example, a multi-channel LPAS coder may be used with microphones that are at some distance apart or with directed microphones that are close together. In some settings, multiple sound sources will be common and inter-channel correlation reduced, while in other settings, a single sound will be predominant. Sometimes, the acoustic setting for each microphone will be similar, in other situations, some microphones may be close to reflective surfaces while others are not. The type and degree of inter-channel and intra-channel signal correlations in these different settings are likely to vary. The coder described in [3] is not always well suited to cope with these different cases.